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Krishna K. Krishnan

Researcher at Wichita State University

Publications -  56
Citations -  761

Krishna K. Krishnan is an academic researcher from Wichita State University. The author has contributed to research in topics: Supply chain & Scheduling (production processes). The author has an hindex of 15, co-authored 56 publications receiving 596 citations. Previous affiliations of Krishna K. Krishnan include University College of Engineering.

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Design of robust layout for Dynamic Plant Layout Problems

TL;DR: In this paper, a robust facility layout is proposed under the dynamic demand environment, which assumes that a layout will accommodate changes from time to time with low rearrangement and production interruption costs, and that the machines can be easily relocated.
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Industry 4.0 in Logistics and Supply Chain Management: A Systematic Literature Review

TL;DR: In this article, the authors proposed a concept of Industry 4.0, which focuses on automation of system and process, digitalization, and data exchange in industries, and their goal is to achieve a smart factory to reduce lead time to respond to requests.
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Effect of variations in the riveting process on the quality of riveted joints

TL;DR: In this paper, the effect of the various parameters associated with a riveting process on the quality of a formed rivet was studied using finite element simulation. And the results indicated that most rivets that are formed will not meet the quality requirements, mainly due to the existence of a gap between the formed rivets and the hole.
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Study of the impact of riveting sequence, rivet pitch, and gap between sheets on the quality of riveted lap joints using finite element method

TL;DR: In this article, the effect of controllable process parameters in riveting (i.e., the sequence of riveting, distance between rivets (pitch), and gap between sheets) on the quality of riveted lap joints and the formed rivets was investigated.
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A simulation-based approach for risk assessment of facility layout designs under stochastic product demands

TL;DR: In this article, a simulation-based method for predicting the uncertainty associated with the layout is presented, and the validation of the simulation approach against analytical procedures is first detailed and then three scenarios of increasing complexity and size are provided.